Title: User-based visual-interactive similarity definition for mixed data objects: concept and first implementation
Authors: Bernard, Jürgen
Sessler, David
Ruppert, Tobbias
Citation: WSCG 2014: communication papers proceedings: 22nd International Conference in Central Europeon Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 329-338.
Issue Date: 2014
Publisher: Václav Skala - UNION Agency
Document type: konferenční příspěvek
URI: wscg.zcu.cz/WSCG2014/!!_2014-WSCG-Communication.pdf
ISBN: 978-80-86943-71-8
Keywords: opatření;návrh zaměřený na uživatele;uživatelská zpětná vazba;smíšené data sety;výběr funkcí;vizualizace informací;vizuální analýza
Keywords in different language: measures;user-centered design;user feedback;mixed data sets;feature selection;information visualization;visual analytics
Abstract in different language: The definition of similarity between data objects plays a key role in many analytical systems. The process of similarity definition comprises several challenges as three main problems occur: different stakeholders, mixed data, and changing requirements. Firstly, in many applications the developers of the analytical system (data scientists) model the similarity, while the users (domain experts) have distinct (mental) similarity notions. Secondly, the definition of similarity for mixed data types is challenging. Thirdly, many systems use static similarity models that cannot adapt to changing data or user needs. We present a concept for the development of systems that support the visual-interactive similarity definition for mixed data objects emphasizing 15 crucial steps. For each step different design considerations and implementation variants are presented, revealing a large design space. Moreover, we present a first implementation of our concept, enabling domain experts to express mental similarity notions through a visual-interactive system. The provided implementation tackles the different-stakeholders problem, the mixed data problem, and the changing requirements problem. The implementation is not limited to a specific mixed data set. However, we show the applicability of our implementation in a case study where a functional similarity model is trained for countries as objects.
Rights: @ Václav Skala - UNION Agency
Appears in Collections:WSCG 2014: Communication Papers Proceedings

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